1. Field
Embodiments relate to an object recognition system and method using a feature extraction algorithm based on a model of human vision.
2. Description of the Related Art
In general, in the existing field of computer vision, object recognition proceeds in the following manner: a database of objects to be recognized is established offline, the objects are registered after training, the registered objects are recognized using a feature extraction algorithm and a recognizer, and determination as to whether the registered objects are present in an image which is currently input is made.
If a three-dimensional CAD model is used to establish the object database, a manual operation may be necessary and thus object feature extraction and registration are not useful in view of an actual robot service. Recently, an object feature extraction and registration technology which does not require a manual operation has been developed, but there is a limitation in providing object recognition that exhibits high resistance to environmental variation.
Environmental variation, as used in relation to object recognition, may be roughly divided into photometric invariance which occurs due to illumination variation, noise or the like and geometric invariance related to variation in camera angle or distance from an object. The reason why invariance elements are of importance is that, since types and features of objects used in homes and by individuals are different in view of a robot service, it may be difficult for an engineer to directly receive a desired list of objects from a user and to register the list in view of privacy protection, and the user may need to register objects. That is, since the user directly trains a robot online or offline with respect to objects, it is troublesome that a large number of images are collected so as to cope with object variation. It may be important to cope with a large amount of variation and to maintain a stable recognition rate through a single registration operation.
However, the existing object recognition system does not exhibit high resistance to environmental variation.